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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 01 May 2010 18:47:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/01/t1272739739a7pbkuf1m028bms.htm/, Retrieved Sat, 27 Apr 2024 23:18:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75159, Retrieved Sat, 27 Apr 2024 23:18:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2010-05-01 18:47:39] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
6550
8728
12026
14395
14587
13791
9498
8251
7049
9545
9364
8456
7237
9374
11837
13784
15926
13821
11143
7975
7610
10015
12759
8816
10677
10947
15200
17010
20900
16205
12143
8997
5568
11474
12256
10583
10862
10965
14405
20379
20128
17816
12268
8642
7962
13932
15936
12628
12267
12470
18944
21259
22015
18581
15175
10306
10792
14752
13754
11738
12181
12965
19990
23125
23541
21247
15189
14767
10895
17130
17697
16611
12674
12760
20249
22135
20677
19933
15388
15113
13401
16135
17562
14720
12225
11608
20985
19692
24081
22114
14220
13434
13598
17187
16119
13713
13210
14251
20139
21725
26099
21084
18024
16722
14385
21342
17180
14577




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75159&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75159&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75159&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7171337.45270
20.3583673.72430.000157
30.0725320.75380.226313
40.0287750.2990.382743
50.1629221.69310.046656
60.2039972.120.018148
70.1354921.40810.080991
8-0.014234-0.14790.441339
90.0112920.11740.453399
100.2563612.66420.00445
110.5938796.17180
120.7626247.92540
130.5476795.69170
140.2290922.38080.009513
15-0.01979-0.20570.418721
16-0.054115-0.56240.287511
170.0941220.97810.165094
180.1011791.05150.147692
190.0480410.49930.309307
20-0.106451-1.10630.135534
21-0.077778-0.80830.210351
220.1478741.53680.063639
230.4548374.72683e-06
240.5867936.09810
250.4102174.26312.2e-05
260.1389851.44440.075764
27-0.093136-0.96790.167628
28-0.102124-1.06130.145461
290.0099280.10320.459007
300.023340.24260.404404
31-0.044894-0.46660.320878
32-0.166577-1.73110.043143
33-0.165021-1.71490.044611
340.0527970.54870.292178
350.3039363.15860.001028
360.4217964.38341.4e-05
370.2593642.69540.004078
380.0274040.28480.388177
39-0.162227-1.68590.04735
40-0.156697-1.62840.053173
41-0.066457-0.69060.245638
42-0.066457-0.69060.245637
43-0.127176-1.32160.094539
44-0.256103-2.66150.004483
45-0.247931-2.57660.005664
46-0.07469-0.77620.219664
470.1389861.44440.075762
480.2242982.3310.010806

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.717133 & 7.4527 & 0 \tabularnewline
2 & 0.358367 & 3.7243 & 0.000157 \tabularnewline
3 & 0.072532 & 0.7538 & 0.226313 \tabularnewline
4 & 0.028775 & 0.299 & 0.382743 \tabularnewline
5 & 0.162922 & 1.6931 & 0.046656 \tabularnewline
6 & 0.203997 & 2.12 & 0.018148 \tabularnewline
7 & 0.135492 & 1.4081 & 0.080991 \tabularnewline
8 & -0.014234 & -0.1479 & 0.441339 \tabularnewline
9 & 0.011292 & 0.1174 & 0.453399 \tabularnewline
10 & 0.256361 & 2.6642 & 0.00445 \tabularnewline
11 & 0.593879 & 6.1718 & 0 \tabularnewline
12 & 0.762624 & 7.9254 & 0 \tabularnewline
13 & 0.547679 & 5.6917 & 0 \tabularnewline
14 & 0.229092 & 2.3808 & 0.009513 \tabularnewline
15 & -0.01979 & -0.2057 & 0.418721 \tabularnewline
16 & -0.054115 & -0.5624 & 0.287511 \tabularnewline
17 & 0.094122 & 0.9781 & 0.165094 \tabularnewline
18 & 0.101179 & 1.0515 & 0.147692 \tabularnewline
19 & 0.048041 & 0.4993 & 0.309307 \tabularnewline
20 & -0.106451 & -1.1063 & 0.135534 \tabularnewline
21 & -0.077778 & -0.8083 & 0.210351 \tabularnewline
22 & 0.147874 & 1.5368 & 0.063639 \tabularnewline
23 & 0.454837 & 4.7268 & 3e-06 \tabularnewline
24 & 0.586793 & 6.0981 & 0 \tabularnewline
25 & 0.410217 & 4.2631 & 2.2e-05 \tabularnewline
26 & 0.138985 & 1.4444 & 0.075764 \tabularnewline
27 & -0.093136 & -0.9679 & 0.167628 \tabularnewline
28 & -0.102124 & -1.0613 & 0.145461 \tabularnewline
29 & 0.009928 & 0.1032 & 0.459007 \tabularnewline
30 & 0.02334 & 0.2426 & 0.404404 \tabularnewline
31 & -0.044894 & -0.4666 & 0.320878 \tabularnewline
32 & -0.166577 & -1.7311 & 0.043143 \tabularnewline
33 & -0.165021 & -1.7149 & 0.044611 \tabularnewline
34 & 0.052797 & 0.5487 & 0.292178 \tabularnewline
35 & 0.303936 & 3.1586 & 0.001028 \tabularnewline
36 & 0.421796 & 4.3834 & 1.4e-05 \tabularnewline
37 & 0.259364 & 2.6954 & 0.004078 \tabularnewline
38 & 0.027404 & 0.2848 & 0.388177 \tabularnewline
39 & -0.162227 & -1.6859 & 0.04735 \tabularnewline
40 & -0.156697 & -1.6284 & 0.053173 \tabularnewline
41 & -0.066457 & -0.6906 & 0.245638 \tabularnewline
42 & -0.066457 & -0.6906 & 0.245637 \tabularnewline
43 & -0.127176 & -1.3216 & 0.094539 \tabularnewline
44 & -0.256103 & -2.6615 & 0.004483 \tabularnewline
45 & -0.247931 & -2.5766 & 0.005664 \tabularnewline
46 & -0.07469 & -0.7762 & 0.219664 \tabularnewline
47 & 0.138986 & 1.4444 & 0.075762 \tabularnewline
48 & 0.224298 & 2.331 & 0.010806 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75159&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.717133[/C][C]7.4527[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.358367[/C][C]3.7243[/C][C]0.000157[/C][/ROW]
[ROW][C]3[/C][C]0.072532[/C][C]0.7538[/C][C]0.226313[/C][/ROW]
[ROW][C]4[/C][C]0.028775[/C][C]0.299[/C][C]0.382743[/C][/ROW]
[ROW][C]5[/C][C]0.162922[/C][C]1.6931[/C][C]0.046656[/C][/ROW]
[ROW][C]6[/C][C]0.203997[/C][C]2.12[/C][C]0.018148[/C][/ROW]
[ROW][C]7[/C][C]0.135492[/C][C]1.4081[/C][C]0.080991[/C][/ROW]
[ROW][C]8[/C][C]-0.014234[/C][C]-0.1479[/C][C]0.441339[/C][/ROW]
[ROW][C]9[/C][C]0.011292[/C][C]0.1174[/C][C]0.453399[/C][/ROW]
[ROW][C]10[/C][C]0.256361[/C][C]2.6642[/C][C]0.00445[/C][/ROW]
[ROW][C]11[/C][C]0.593879[/C][C]6.1718[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.762624[/C][C]7.9254[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.547679[/C][C]5.6917[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.229092[/C][C]2.3808[/C][C]0.009513[/C][/ROW]
[ROW][C]15[/C][C]-0.01979[/C][C]-0.2057[/C][C]0.418721[/C][/ROW]
[ROW][C]16[/C][C]-0.054115[/C][C]-0.5624[/C][C]0.287511[/C][/ROW]
[ROW][C]17[/C][C]0.094122[/C][C]0.9781[/C][C]0.165094[/C][/ROW]
[ROW][C]18[/C][C]0.101179[/C][C]1.0515[/C][C]0.147692[/C][/ROW]
[ROW][C]19[/C][C]0.048041[/C][C]0.4993[/C][C]0.309307[/C][/ROW]
[ROW][C]20[/C][C]-0.106451[/C][C]-1.1063[/C][C]0.135534[/C][/ROW]
[ROW][C]21[/C][C]-0.077778[/C][C]-0.8083[/C][C]0.210351[/C][/ROW]
[ROW][C]22[/C][C]0.147874[/C][C]1.5368[/C][C]0.063639[/C][/ROW]
[ROW][C]23[/C][C]0.454837[/C][C]4.7268[/C][C]3e-06[/C][/ROW]
[ROW][C]24[/C][C]0.586793[/C][C]6.0981[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.410217[/C][C]4.2631[/C][C]2.2e-05[/C][/ROW]
[ROW][C]26[/C][C]0.138985[/C][C]1.4444[/C][C]0.075764[/C][/ROW]
[ROW][C]27[/C][C]-0.093136[/C][C]-0.9679[/C][C]0.167628[/C][/ROW]
[ROW][C]28[/C][C]-0.102124[/C][C]-1.0613[/C][C]0.145461[/C][/ROW]
[ROW][C]29[/C][C]0.009928[/C][C]0.1032[/C][C]0.459007[/C][/ROW]
[ROW][C]30[/C][C]0.02334[/C][C]0.2426[/C][C]0.404404[/C][/ROW]
[ROW][C]31[/C][C]-0.044894[/C][C]-0.4666[/C][C]0.320878[/C][/ROW]
[ROW][C]32[/C][C]-0.166577[/C][C]-1.7311[/C][C]0.043143[/C][/ROW]
[ROW][C]33[/C][C]-0.165021[/C][C]-1.7149[/C][C]0.044611[/C][/ROW]
[ROW][C]34[/C][C]0.052797[/C][C]0.5487[/C][C]0.292178[/C][/ROW]
[ROW][C]35[/C][C]0.303936[/C][C]3.1586[/C][C]0.001028[/C][/ROW]
[ROW][C]36[/C][C]0.421796[/C][C]4.3834[/C][C]1.4e-05[/C][/ROW]
[ROW][C]37[/C][C]0.259364[/C][C]2.6954[/C][C]0.004078[/C][/ROW]
[ROW][C]38[/C][C]0.027404[/C][C]0.2848[/C][C]0.388177[/C][/ROW]
[ROW][C]39[/C][C]-0.162227[/C][C]-1.6859[/C][C]0.04735[/C][/ROW]
[ROW][C]40[/C][C]-0.156697[/C][C]-1.6284[/C][C]0.053173[/C][/ROW]
[ROW][C]41[/C][C]-0.066457[/C][C]-0.6906[/C][C]0.245638[/C][/ROW]
[ROW][C]42[/C][C]-0.066457[/C][C]-0.6906[/C][C]0.245637[/C][/ROW]
[ROW][C]43[/C][C]-0.127176[/C][C]-1.3216[/C][C]0.094539[/C][/ROW]
[ROW][C]44[/C][C]-0.256103[/C][C]-2.6615[/C][C]0.004483[/C][/ROW]
[ROW][C]45[/C][C]-0.247931[/C][C]-2.5766[/C][C]0.005664[/C][/ROW]
[ROW][C]46[/C][C]-0.07469[/C][C]-0.7762[/C][C]0.219664[/C][/ROW]
[ROW][C]47[/C][C]0.138986[/C][C]1.4444[/C][C]0.075762[/C][/ROW]
[ROW][C]48[/C][C]0.224298[/C][C]2.331[/C][C]0.010806[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75159&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75159&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7171337.45270
20.3583673.72430.000157
30.0725320.75380.226313
40.0287750.2990.382743
50.1629221.69310.046656
60.2039972.120.018148
70.1354921.40810.080991
8-0.014234-0.14790.441339
90.0112920.11740.453399
100.2563612.66420.00445
110.5938796.17180
120.7626247.92540
130.5476795.69170
140.2290922.38080.009513
15-0.01979-0.20570.418721
16-0.054115-0.56240.287511
170.0941220.97810.165094
180.1011791.05150.147692
190.0480410.49930.309307
20-0.106451-1.10630.135534
21-0.077778-0.80830.210351
220.1478741.53680.063639
230.4548374.72683e-06
240.5867936.09810
250.4102174.26312.2e-05
260.1389851.44440.075764
27-0.093136-0.96790.167628
28-0.102124-1.06130.145461
290.0099280.10320.459007
300.023340.24260.404404
31-0.044894-0.46660.320878
32-0.166577-1.73110.043143
33-0.165021-1.71490.044611
340.0527970.54870.292178
350.3039363.15860.001028
360.4217964.38341.4e-05
370.2593642.69540.004078
380.0274040.28480.388177
39-0.162227-1.68590.04735
40-0.156697-1.62840.053173
41-0.066457-0.69060.245638
42-0.066457-0.69060.245637
43-0.127176-1.32160.094539
44-0.256103-2.66150.004483
45-0.247931-2.57660.005664
46-0.07469-0.77620.219664
470.1389861.44440.075762
480.2242982.3310.010806







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7171337.45270
2-0.320992-3.33580.000583
3-0.084386-0.8770.191225
40.2518172.6170.005072
50.201442.09340.019326
6-0.216654-2.25150.013188
7-0.04635-0.48170.315501
8-0.001304-0.01350.494608
90.3246953.37430.000514
100.3645523.78850.000125
110.3802323.95156.9e-05
120.1603281.66620.049288
13-0.345716-3.59280.000247
14-0.075842-0.78820.216161
15-0.030126-0.31310.377412
16-0.129661-1.34750.090323
170.1275961.3260.093816
18-0.211572-2.19870.015015
190.1378161.43220.077483
20-0.092113-0.95730.170285
210.0446740.46430.321695
22-0.053693-0.5580.289
230.1107561.1510.126134
24-0.045493-0.47280.318663
250.0269570.28020.389949
260.0053390.05550.477929
27-0.054316-0.56450.286803
28-0.054829-0.56980.284998
290.0197580.20530.418848
30-0.067379-0.70020.242648
310.0056910.05910.476473
320.064110.66630.253334
33-0.142173-1.47750.071225
340.00760.0790.468598
35-0.000554-0.00580.497708
36-0.061407-0.63820.262361
37-0.058542-0.60840.272105
380.0456540.47440.318069
390.0269490.28010.389981
40-0.058452-0.60750.272413
410.0202430.21040.416887
42-0.108784-1.13050.130382
430.0314150.32650.372348
44-0.047442-0.4930.311495
45-0.059545-0.61880.268671
46-0.108206-1.12450.131646
470.0166270.17280.431568
48-0.087205-0.90630.183409

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.717133 & 7.4527 & 0 \tabularnewline
2 & -0.320992 & -3.3358 & 0.000583 \tabularnewline
3 & -0.084386 & -0.877 & 0.191225 \tabularnewline
4 & 0.251817 & 2.617 & 0.005072 \tabularnewline
5 & 0.20144 & 2.0934 & 0.019326 \tabularnewline
6 & -0.216654 & -2.2515 & 0.013188 \tabularnewline
7 & -0.04635 & -0.4817 & 0.315501 \tabularnewline
8 & -0.001304 & -0.0135 & 0.494608 \tabularnewline
9 & 0.324695 & 3.3743 & 0.000514 \tabularnewline
10 & 0.364552 & 3.7885 & 0.000125 \tabularnewline
11 & 0.380232 & 3.9515 & 6.9e-05 \tabularnewline
12 & 0.160328 & 1.6662 & 0.049288 \tabularnewline
13 & -0.345716 & -3.5928 & 0.000247 \tabularnewline
14 & -0.075842 & -0.7882 & 0.216161 \tabularnewline
15 & -0.030126 & -0.3131 & 0.377412 \tabularnewline
16 & -0.129661 & -1.3475 & 0.090323 \tabularnewline
17 & 0.127596 & 1.326 & 0.093816 \tabularnewline
18 & -0.211572 & -2.1987 & 0.015015 \tabularnewline
19 & 0.137816 & 1.4322 & 0.077483 \tabularnewline
20 & -0.092113 & -0.9573 & 0.170285 \tabularnewline
21 & 0.044674 & 0.4643 & 0.321695 \tabularnewline
22 & -0.053693 & -0.558 & 0.289 \tabularnewline
23 & 0.110756 & 1.151 & 0.126134 \tabularnewline
24 & -0.045493 & -0.4728 & 0.318663 \tabularnewline
25 & 0.026957 & 0.2802 & 0.389949 \tabularnewline
26 & 0.005339 & 0.0555 & 0.477929 \tabularnewline
27 & -0.054316 & -0.5645 & 0.286803 \tabularnewline
28 & -0.054829 & -0.5698 & 0.284998 \tabularnewline
29 & 0.019758 & 0.2053 & 0.418848 \tabularnewline
30 & -0.067379 & -0.7002 & 0.242648 \tabularnewline
31 & 0.005691 & 0.0591 & 0.476473 \tabularnewline
32 & 0.06411 & 0.6663 & 0.253334 \tabularnewline
33 & -0.142173 & -1.4775 & 0.071225 \tabularnewline
34 & 0.0076 & 0.079 & 0.468598 \tabularnewline
35 & -0.000554 & -0.0058 & 0.497708 \tabularnewline
36 & -0.061407 & -0.6382 & 0.262361 \tabularnewline
37 & -0.058542 & -0.6084 & 0.272105 \tabularnewline
38 & 0.045654 & 0.4744 & 0.318069 \tabularnewline
39 & 0.026949 & 0.2801 & 0.389981 \tabularnewline
40 & -0.058452 & -0.6075 & 0.272413 \tabularnewline
41 & 0.020243 & 0.2104 & 0.416887 \tabularnewline
42 & -0.108784 & -1.1305 & 0.130382 \tabularnewline
43 & 0.031415 & 0.3265 & 0.372348 \tabularnewline
44 & -0.047442 & -0.493 & 0.311495 \tabularnewline
45 & -0.059545 & -0.6188 & 0.268671 \tabularnewline
46 & -0.108206 & -1.1245 & 0.131646 \tabularnewline
47 & 0.016627 & 0.1728 & 0.431568 \tabularnewline
48 & -0.087205 & -0.9063 & 0.183409 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75159&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.717133[/C][C]7.4527[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.320992[/C][C]-3.3358[/C][C]0.000583[/C][/ROW]
[ROW][C]3[/C][C]-0.084386[/C][C]-0.877[/C][C]0.191225[/C][/ROW]
[ROW][C]4[/C][C]0.251817[/C][C]2.617[/C][C]0.005072[/C][/ROW]
[ROW][C]5[/C][C]0.20144[/C][C]2.0934[/C][C]0.019326[/C][/ROW]
[ROW][C]6[/C][C]-0.216654[/C][C]-2.2515[/C][C]0.013188[/C][/ROW]
[ROW][C]7[/C][C]-0.04635[/C][C]-0.4817[/C][C]0.315501[/C][/ROW]
[ROW][C]8[/C][C]-0.001304[/C][C]-0.0135[/C][C]0.494608[/C][/ROW]
[ROW][C]9[/C][C]0.324695[/C][C]3.3743[/C][C]0.000514[/C][/ROW]
[ROW][C]10[/C][C]0.364552[/C][C]3.7885[/C][C]0.000125[/C][/ROW]
[ROW][C]11[/C][C]0.380232[/C][C]3.9515[/C][C]6.9e-05[/C][/ROW]
[ROW][C]12[/C][C]0.160328[/C][C]1.6662[/C][C]0.049288[/C][/ROW]
[ROW][C]13[/C][C]-0.345716[/C][C]-3.5928[/C][C]0.000247[/C][/ROW]
[ROW][C]14[/C][C]-0.075842[/C][C]-0.7882[/C][C]0.216161[/C][/ROW]
[ROW][C]15[/C][C]-0.030126[/C][C]-0.3131[/C][C]0.377412[/C][/ROW]
[ROW][C]16[/C][C]-0.129661[/C][C]-1.3475[/C][C]0.090323[/C][/ROW]
[ROW][C]17[/C][C]0.127596[/C][C]1.326[/C][C]0.093816[/C][/ROW]
[ROW][C]18[/C][C]-0.211572[/C][C]-2.1987[/C][C]0.015015[/C][/ROW]
[ROW][C]19[/C][C]0.137816[/C][C]1.4322[/C][C]0.077483[/C][/ROW]
[ROW][C]20[/C][C]-0.092113[/C][C]-0.9573[/C][C]0.170285[/C][/ROW]
[ROW][C]21[/C][C]0.044674[/C][C]0.4643[/C][C]0.321695[/C][/ROW]
[ROW][C]22[/C][C]-0.053693[/C][C]-0.558[/C][C]0.289[/C][/ROW]
[ROW][C]23[/C][C]0.110756[/C][C]1.151[/C][C]0.126134[/C][/ROW]
[ROW][C]24[/C][C]-0.045493[/C][C]-0.4728[/C][C]0.318663[/C][/ROW]
[ROW][C]25[/C][C]0.026957[/C][C]0.2802[/C][C]0.389949[/C][/ROW]
[ROW][C]26[/C][C]0.005339[/C][C]0.0555[/C][C]0.477929[/C][/ROW]
[ROW][C]27[/C][C]-0.054316[/C][C]-0.5645[/C][C]0.286803[/C][/ROW]
[ROW][C]28[/C][C]-0.054829[/C][C]-0.5698[/C][C]0.284998[/C][/ROW]
[ROW][C]29[/C][C]0.019758[/C][C]0.2053[/C][C]0.418848[/C][/ROW]
[ROW][C]30[/C][C]-0.067379[/C][C]-0.7002[/C][C]0.242648[/C][/ROW]
[ROW][C]31[/C][C]0.005691[/C][C]0.0591[/C][C]0.476473[/C][/ROW]
[ROW][C]32[/C][C]0.06411[/C][C]0.6663[/C][C]0.253334[/C][/ROW]
[ROW][C]33[/C][C]-0.142173[/C][C]-1.4775[/C][C]0.071225[/C][/ROW]
[ROW][C]34[/C][C]0.0076[/C][C]0.079[/C][C]0.468598[/C][/ROW]
[ROW][C]35[/C][C]-0.000554[/C][C]-0.0058[/C][C]0.497708[/C][/ROW]
[ROW][C]36[/C][C]-0.061407[/C][C]-0.6382[/C][C]0.262361[/C][/ROW]
[ROW][C]37[/C][C]-0.058542[/C][C]-0.6084[/C][C]0.272105[/C][/ROW]
[ROW][C]38[/C][C]0.045654[/C][C]0.4744[/C][C]0.318069[/C][/ROW]
[ROW][C]39[/C][C]0.026949[/C][C]0.2801[/C][C]0.389981[/C][/ROW]
[ROW][C]40[/C][C]-0.058452[/C][C]-0.6075[/C][C]0.272413[/C][/ROW]
[ROW][C]41[/C][C]0.020243[/C][C]0.2104[/C][C]0.416887[/C][/ROW]
[ROW][C]42[/C][C]-0.108784[/C][C]-1.1305[/C][C]0.130382[/C][/ROW]
[ROW][C]43[/C][C]0.031415[/C][C]0.3265[/C][C]0.372348[/C][/ROW]
[ROW][C]44[/C][C]-0.047442[/C][C]-0.493[/C][C]0.311495[/C][/ROW]
[ROW][C]45[/C][C]-0.059545[/C][C]-0.6188[/C][C]0.268671[/C][/ROW]
[ROW][C]46[/C][C]-0.108206[/C][C]-1.1245[/C][C]0.131646[/C][/ROW]
[ROW][C]47[/C][C]0.016627[/C][C]0.1728[/C][C]0.431568[/C][/ROW]
[ROW][C]48[/C][C]-0.087205[/C][C]-0.9063[/C][C]0.183409[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75159&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75159&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7171337.45270
2-0.320992-3.33580.000583
3-0.084386-0.8770.191225
40.2518172.6170.005072
50.201442.09340.019326
6-0.216654-2.25150.013188
7-0.04635-0.48170.315501
8-0.001304-0.01350.494608
90.3246953.37430.000514
100.3645523.78850.000125
110.3802323.95156.9e-05
120.1603281.66620.049288
13-0.345716-3.59280.000247
14-0.075842-0.78820.216161
15-0.030126-0.31310.377412
16-0.129661-1.34750.090323
170.1275961.3260.093816
18-0.211572-2.19870.015015
190.1378161.43220.077483
20-0.092113-0.95730.170285
210.0446740.46430.321695
22-0.053693-0.5580.289
230.1107561.1510.126134
24-0.045493-0.47280.318663
250.0269570.28020.389949
260.0053390.05550.477929
27-0.054316-0.56450.286803
28-0.054829-0.56980.284998
290.0197580.20530.418848
30-0.067379-0.70020.242648
310.0056910.05910.476473
320.064110.66630.253334
33-0.142173-1.47750.071225
340.00760.0790.468598
35-0.000554-0.00580.497708
36-0.061407-0.63820.262361
37-0.058542-0.60840.272105
380.0456540.47440.318069
390.0269490.28010.389981
40-0.058452-0.60750.272413
410.0202430.21040.416887
42-0.108784-1.13050.130382
430.0314150.32650.372348
44-0.047442-0.4930.311495
45-0.059545-0.61880.268671
46-0.108206-1.12450.131646
470.0166270.17280.431568
48-0.087205-0.90630.183409



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')